In 2025, Buildcheck officially launched after raising $5.9 million in seed funding—with help from Uncork Capital, Peterson Ventures, XFund, and founders and senior executives at OpenAI, Opendoor, CBRE, Zillow and more.

Michalatos sat down with Construction Executive to discuss the rigorous creative and prototyping process for this product, how he expects the technology to evolve over the next decade, as well as many details in between.

What type of technology is Buildcheck?

Buildcheck is an AI-powered design review platform. We’ve trained computer vision models to read construction drawings—the language of construction—so we can catch coordination errors, missing scope and cross-discipline conflicts before they turn into RFIs, change orders or city comments. We work with real estate developers, general contractors and design firms, and our customers typically see a 10x to 40x return on what they spend with us.

What was the impetus for creating Buildcheck?

The impetus is personal. I grew up in a construction family in Vancouver—my father built single-family homes for decades—and I spent my own career on the owner, general contractor and design sides: Stantec, Honeywell, EllisDon on hospital design-builds and QuadReal on mixed-use development. Across every one of those roles, I kept seeing the same pattern: small inconsistencies scattered across hundreds of sheets that nobody caught until steel was going up or concrete was being poured. Globally, that’s a $200-billion problem. When I stepped back, it was obvious: Construction doesn’t run on contracts or emails, it runs on drawings. Until AI could actually read the lines on a sheet, it was going to stay peripheral to real construction risk. That’s what Buildcheck is built to solve.

Who is Buildcheck’s main type of client within construction?

Primarily general contractors and real estate developers, with a growing number of architecture and engineering firms using us as an internal QA/QC layer. Our customers include EllisDon, AvalonBay, Novo Construction, Dempsey Construction and many more.

The common thread is that they’re all managing design risk—not just building. That’s a bigger group than it used to be. Public infrastructure is increasingly delivered through design-build and alliance contracts, which push design responsibility onto contractors. Mid-market developers are engaging general contractors earlier through preconstruction services or GMP structures. Architects are carrying more professional liability exposure on bigger, more complex drawing sets. All of them share the same underlying need: find the coordination gaps before they get priced into a change order.

We tend to fit best with firms that have already decided design coordination is a bottleneck. They usually know exactly where it hurts; our job is to show them that AI can now do something about it.

Do you work with clients outside of construction?

No, and that’s intentional. Computer vision on construction drawings is a uniquely hard problem—drawings aren’t standardized, symbol sets vary by firm and discipline, and layering conventions shift project to project. Training a model that genuinely understands an MEP sheet versus a structural sheet or civil sheet takes years of labeled data and domain expertise. That depth is the moat, and it only comes from staying focused.

That said, the underlying technology could apply to other drawing-heavy industries—shipbuilding, aerospace manufacturing and certain industrial engineering verticals. For now, the opportunity in construction alone is enormous. The global design-error problem is $200 billion annually and nobody has solved it. We’d rather be the best in the world at one thing than average at several.

Do you still run into problems with designers/companies hesitant to use AI for preconstruction? How do you create buy-in/convince them to get onboard in the first place?

Yes, and I think that skepticism is healthy. There’s a lot of AI-washing in construction tech right now and buyers are right to demand proof.

For our clients, a demo is the starting point, but the real conversation begins when we run their drawings through Buildcheck. In most cases, we come back with dozens to hundreds of flagged issues that their experienced team hadn’t caught. If that first project lands, a companywide rollout tends to follow naturally. We also invite any prospective customers to talk to current customers and hear directly from them, not us.

The other piece is framing. We aren’t replacing labor; we’re enabling your people to do more. Your senior reviewers still make the judgment calls. We just compress the hours of repetitive pattern-matching work—the missing power, the mismatched fire ratings, the clashing service connections—so your people can spend their time on the decisions that actually require expertise. When buyers understand that, the skepticism usually shifts from “will this work?” to “how fast can we roll it out?”

Does this type of tech only apply to the preconstruction process?

Preconstruction is where we start because that’s where the ROI is most obvious. Catching a coordination issue on a sheet costs almost nothing to fix; catching it in the field can cost six figures and weeks of schedule. Front-end planning research from the Construction Industry Institute has consistently shown returns of roughly 10:1 on investment in document quality before construction.

But computer vision on drawings unlocks workflows across the entire project lifecycle, such as shop drawing cross-checks against the IFC set, change-order quantification, automated takeoffs and, eventually, as-built verification. The same underlying models that detect errors today can drive proactive design improvement tomorrow—through real-time coordination feedback as drawings and design optimization evolve.

The long-term vision is that drawings stop being static PDFs and start being structured, machine-readable artifacts. Once that happens, everything downstream—estimating, procurement, coordination, closeout—gets meaningfully faster.

What was the development/prototyping process like for getting this product out the door?

Our process was and continues to be rigorous and disciplined. We’ve spent over three years building proprietary models trained specifically for construction drawings, but also building the user experience around it. Neither of these can be vibecoded because the domain expertise and customer feedback loops take time to establish.

Two things shaped the process. First, we chose quality at every step—from labeling the data and fine-tuning the models to having construction experts verify every AI output before it reaches the customer. Second, our earliest customers did more to shape the user experience than any internal plan ever could have. General contractors and developers willing to give us feedback are how we figured out what reviewers actually want to see first, how to surface severity and how the interface should mirror the way their teams already work.

How has this type of technology evolved since Buildcheck’s inception? Where do you see it going by the next decade?

When we started, most construction AI was optical character recognition, chatbots layered over contract text or basic clash detection inside a BIM model. Useful, but peripheral to the core risk. The shift over the last two years has been toward specialized vision models that can actually interpret 2D drawings—the medium construction still overwhelmingly runs on.

Looking out ten years, I’d expect three things. First, error detection becomes table stakes—every major project will run through automated review the same way it runs through code check today. Second, the tooling moves from reactive to proactive: Rather than flagging problems after a set is issued, AI will provide real-time coordination feedback inside the design-authoring tools as drawings evolve. Third, we’ll start to see genuine design optimization—AI that suggests smaller duct runs, more efficient structural layouts and value engineering moves grounded in both code and constructability.

Is there fear that this type of AI will ‘take people’s jobs’?

It comes up and it deserves an answer. AI isn’t going to replace most construction jobs—it won’t sequence concrete pours, negotiate a subcontract or lead a toolbox talk. Leadership and judgment in construction remain deeply human. And besides, there is a huge backlog of work for the entire industry. We want to do more and technology enables that; we can’t afford to lose people.

What AI removes is the repetitive, pattern-based review work that consumes hours: hunting missing dimensions across 400 sheets, cross-referencing fire ratings, chasing broken callouts. Given the industry’s labor gap and flat productivity, the real risk isn’t AI taking jobs. It’s the industry being unable to deliver enough projects, affordably, because we can’t scale human expertise fast enough. AI is a leverage tool for the people already here.

How has this tech saved money, time, safety, productivity?

Money and time are the easiest to quantify. Design errors and coordination gaps drive an estimated $200 billion in global overages annually. On individual projects, we regularly see six-figure savings and multi-week schedule protection—on one 230-unit multifamily project, over $500,000 in cost avoidance and 27 days of schedule saved. Under conservative assumptions, customers see 10-40x ROI.

Safety is the most underappreciated. The highest-severity inconsistencies we catch are life-safety issues—mismatched fire ratings between disciplines, undersized electrical feeds to fire pumps and missing sprinkler branches. Finding those in the documents, before installation, is meaningfully better than catching them at commissioning.

Do you believe this type of technology is gaining momentum within the industry? Is it helping give AI a friendlier reputation within construction?

Yes, clearly. Recent industry surveys show up to 64% of construction organizations experimenting with AI. Two years ago, the first meeting was about, “Does this work on drawings at all?”

Today it’s about which vendor, what pilot structure, what rollout. That’s a meaningful shift.Construction is actually one of the better industries for AI to land in, because it’s pragmatic. Professionals don’t care about hype—they care about dollars saved, days saved and risk reduced. When they see AI flag a real issue on a real drawing set, skepticism fades quickly. The caveat: Overpromising vendors can set the category back. The industry has a long memory for broken tech promises.

Anything else?

Don’t conflate AI with LLMs. A lot of construction buyers assume ChatGPT-style tools are what AI looks like. Those models are excellent at text—contracts, specs, RFIs—but construction’s highest-value problems are visual: drawings, models, site conditions. The vendors solving those problems are doing specialized computer vision work that looks very different from a chatbot wrapper. When you’re evaluating AI tools, the first question to ask is what the models were actually trained on.

SEE ALSO: SIX AI SOLUTIONS DRIVING PRODUCTIVITY AND PROFITABILITY IN CONSTRUCTION OFFICES

The post A New Vision for AI: Construction Design-Review Platform Lends Extra Eye to Image Analysis first appeared on Construction Executive.

Traditional AI vs. Generative AI

According to the United States Chamber of Commerce, traditional AI is defined as “a subset of artificial intelligence that focuses on performing preset tasks using predetermined algorithms and rules. These AI applications are designed to excel in a single activity or a restricted set of tasks, such as playing chess, diagnosing diseases or translating languages.” Most of us are using traditional AI on an everyday basis when we utilize the Siri function on our iPhones or the Alexa or Google virtual assistants. Indeed, even the filters on your email or phone preventing spam emails or calls from reaching you are forms of conventional AI.

In construction, contractors, suppliers and designers already use traditional AI in troubleshooting technical issues, training, reviewing credit applications or in evaluating a building’s intended use in order to make recommendations for a design or type of material or equipment.

Generative AI differs from traditional in that it emulates human learning and decision-making in order to develop new content. Unlike traditional AI which analyzes existing data, generative AI reuses what it knows to solve new problems. In the construction industry, generative AI is useful in preparing contracts, cost estimates, developing RFPs and scheduling, among other things.

Contract Negotiation and Drafting

Many aspects of a construction contract negotiation can be enhanced by the use of an appropriate AI tool. For example, specialized construction industry AI tools such as Document Crunch and Spellbook can analyze historical negotiation outcomes and provide input as to where the project participant can most benefit from a modification of a contract term. AI can then suggest alternate wording to address the specific issue of concern.

Generative AI tools can likewise be trained on a construction lawyer’s database of contracts and used to efficiently draft new contracts. AI can quickly and efficiently locate and suggest oft-used clauses from previous contracts or other sources. This method can be helpful in promoting consistency across a field of project documents by using standardized wording and by automating repetitive drafting tasks. Using AI in this way serves to reduce human error and reduce hours spent on time-consuming proofreading and cross-checking.

Construction contract drafting is also enhanced when an AI tool is used to identify ambiguous language, conflicts or unfair risk allocation. These methods can assist in avoiding disputes down the road.

Moreover, AI tools can be very effective in drafting individual contract clauses because a user can input prompts for the type of clause they are looking for; the AI tool will then quickly offer intelligent suggestions for contract language that is responsive to and inclusive of the information with which it was provided. For example, a user can request that AI develop a customized payment terms clause that considers that the project is anticipating funding at a particular time or upon a specific event. Using AI to create a first draft to address unique project terms (that is then edited and revised by a human lawyer) is a best practice proven to save costly attorney time.

The better developed the input, the better the result achieved in the output. That is, more detailed and specific parameters provided to the AI tool will result in higher quality output. Instead of asking AI to create a form subcontract, a user should include parameters in the request detailing that they need a form of steel erection subcontract for an a office building project of 50,000 square feet that is being constructed from ground up on an existing slab in a cold weather climate with a six month duration. Utilizing this method will result in an end product that is much more useful.

AI can then be used further to highlight inconsistencies with other contract documents. Because construction projects typically require multiple documents to create the whole of the “contract documents,” AI can provide substantial value in coordinating the contract document set. Caution should be used in relying on AI output, however, because generative AI cannot be trusted to consider unique project features or relationships.

Other contract drafting and negotiating efficiencies come from AI tools that allow real-time drafting collaboration, redlining, digital document execution and identification, and management of edits to conform content.

Contract Administration

AI is also an incredibly useful tool in construction contract administration, and its potential uses are widespread. It can assist in project planning and scheduling using data from past performance, as well as weather analysis and data about the availability of materials to create an efficient and attainable schedule. Coordination of trades using a schedule analysis can be performed by an AI tool. AI can assist in change-order and submittal tracking. It can review potential project risks and plan mitigation strategies in advance. It can analyze project specifications and use them to create realistic cost estimates for use in budgeting and project planning.  It can evaluate images to assess work quality and identify defects or deviations. AI tools can also decipher and summarize key contract terms and answer contract-related questions. Finally, AI can be used to draft and deploy contractually required notices and directives. All of this enhances communication and collaboration among project participants, the recipe for a successful project.

Inherent Dangers of Using Generative AI

Dangers arise when the data provided to the AI tool is incomplete, inconsistent or low-quality, not uncommon in construction projects. Indeed, the typical construction contract relies on data from multiple sources including design documents, site reports, contractor and subcontractor bids and owner requirements; errors and inaccuracies occur regularly. To avoid this risk, robust quality control of the information provided to the AI tool is imperative. Careful review and human judgment remain necessary because AI is not a substitute for human expertise and experience.

Although the output produced by generative AI can be very convincing and accurate, sometimes the information is just wrong. AI should not be used as anything other than as a preliminary resource for information that must be vetted. Its output must be verified using known and established sources. As an example, using generative AI to respond to an RFI is dangerous. AI can invent incorrect details or specifications that facially appear accurate but are technically incorrect. In order to prevent errors like this, human oversight is absolutely essential. In fact, in 2024, the American Society of Civil Engineers issued a policy statement cautioning that AI cannot replace the professional judgment of the human engineer.

While the use of AI in construction contracting may be hampered by obstacles such as lack of cost, lack of data integration, hallucinations and resistance from industry participants, its usefulness has the potential to far outweigh the barriers. Using AI in construction contracting will be driven forward by the anticipated efficiencies, availability of technology and presence of technology-savvy newcomers to the field. The ultimate result—improvement in project performance. As such AI tools are a welcome advancement in construction contracting.

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The post The Use of AI in Construction Contracts: Do the Pros Outweigh the Cons? first appeared on Construction Executive.

Recent research from CBIZ and The National Center for the Middle Market found that while 31% of construction-industry respondents named increasing efficiency as a top strategic priority (more than any other industry), only 26% of construction firms cited investing in technology as a priority. This begs the question: Where do construction leaders see these efficiency gains coming from if not from technology investments?

This discrepancy represents a general mistrust of modernization in the construction industry. While it’s unlikely robots will take over jobsites altogether, the truth is that software, AI and other technological advancements are powering growth in the construction industry by helping with offsite tasks like material management, financial processes, administrative duties, and safety and compliance. These tools can enhance employees’ capabilities, free up time spent on repetitive tasks and increase efficiency enterprisewide.

Construction firms looking to enhance efficiency should consider the following tech tools:

Artificial Intelligence

AI can help construction firms reduce rework and expedite timelines every step of the way, both onsite and in-office.

AI can:

• Help estimate costs and promote more competitive bids by analyzing historical data, material prices and labor availability
• Avoid turning preventable hiccups into change orders by identifying sequences related to scheduling and issuing alerts regarding material availability
• Track progress, ensure compliance and oversee quality assurance programs
• Reduce repetitive work, manual tasks and time spent preparing reports
• Analyze jobsite photos to flag potential safety risks (i.e., missing PPE or hazards)

It’s important to note that AI’s output is only as good as the data it receives, so firms should prioritize clean data, consistent coding structures and clear governance to ensure reliable insights. Try starting with a narrow, high-value use case—such as AI-powered invoice coding or photo-based progress tracking—then prove the ROI and scale to adjacent workflows.

Enterprise Resource Planning

An ERP centralizes data to promote accessibility, integrates and shares information across departments for greater visibility, and provides real-time insights to help leaders make timely and informed decisions. The right ERP should become the source of truth for operational and financial data across estimating, procurement, project management, accounting and HR/payroll.

ERPs can also:

• Deliver cloud-based service to reduce burdens on in-house IT teams
• Ease demands related to construction-specific workflows
• Provide a single access point for key information from across various systems
• Track inventory
• Help with project management and job costing
• Deliver comprehensive audit trails, apply strong controls and streamline reporting processes

Look for solutions that integrate with field applications (i.e., timekeeping and daily reports), support mobile approvals and offer configurable workflows. Robust role-based permissions, embedded analytics and standardized dashboards can help executives and PMs make faster, more informed decisions. Consider mapping your current processes and pain points, identifying essential features and piloting with real data. Plan for data migration and change management upfront to avoid operational disruption.

Drone Technology

Many construction firms are already using drones to monitor jobsites. These drones can also use advanced sensors to chart out obstructions underground. Eventually, there could be the potential for additional functionality to actively analyze and identify potential code violations as they occur.

Building Information Modeling

BIM software can also help teams visualize what hasn’t been built yet, with some systems even enabling teams to test materials and methods virtually. 4D (time-based) and 5D (cost-based) simulations can help teams evaluate sequencing and budget impacts before mobilization.

Time for Change

When implementing new technologies, there are bound to be growing pains. The process of updating and modernizing systems will always be different for each company due to each having uniquely complex processes and distinct goals. In order to ensure that implementation is successful, a strategic approach to change management is crucial.

Change management refers to the process of aligning leadership on important changes and communicating the value of the changes with employees. This usually involves engaging professionals to formalize the changes and develop a strategic approach to introducing new systems and processes.

Change management is effective when employees feel empowered to contribute to a successful implementation. By helping employees understand the benefits the changes represent, they should feel excited to be able to contribute to the company in a new way.

Implementation Tips

• Make change incremental by breaking implementation into phases.
• Establish baseline KPIs and track improvements.
• Consider field input during design to avoid workarounds and unsuccessful adoption.
• Define data ownership, retention and access controls across internal teams and vendors.
• Implement role-based access and multifactor authentication.
• Fund training and provide support for employees during the initial rollout.

Technology is not a silver bullet for the construction industry’s challenges, but it is a practical lever for boosting efficiency, improving safety and protecting margins. Firms that pair targeted tools (AI, ERPs, drones and BIM) with disciplined change management can capture measurable gains: fewer change orders, faster cycles, better visibility and safer jobsites. Start small with a high-impact pilot, invest in training and track outcomes. With a clear roadmap and an empowered workforce, construction companies can support the craft at the heart of the industry while operating with the speed and precision today’s market demands.

SEE ALSO: WHICH CONSTRUCTION TECHNOLOGY INVESTMENTS ACTUALLY MOVE THE NEEDLE ON PROFITABILITY

The post Practical Technology Upgrades for Construction Firms to Improve Efficiency first appeared on Construction Executive.

From technology’s ever-increasing enmeshment with the construction workforce to persistent data-siloing issues and more, Jon Fingland, vice president and category general manager at Trimble, sat down with Construction Executive to reveal the findings of this first-ever study.

The throughline of this survey seems to be the enmeshment of construction technology and the workforce. How have you seen construction technology and the workforce become more intertwined as technology develops and the workforce shortage worsens? 

I lived through the move to the cloud, the transition to mobile devices. Now we’re living through the age of AI. If I rewind to getting paper cuts from blueprints—that’s how old I am—then fast forward to today’s ability to have the latest drawing set available at the touch of a device in the field, that seems profound. That was one of the first big problems we had to solve in the industry: making sure people are working off current data.

I think what’s interesting about this moment in time is that you need some outside factors to really get people serious and honest about making the change of how they deliver the project and how they process internally. If you look at what’s happening in our market right now, it’s all coming to a head of supply-chain pressures and tariffs and workforce shortages.

We need a half million more workers this year. And 40% of the workforce is going to retire in the next five years. Combine the complexity of the work with the pressures on the supply chain and you start to see signals of shifts even in how people contract work.

They just don’t have enough workers. It’s a real problem—they must figure out how to do more with less and how to collaborate and create more predictable construction. That’s where this survey really comes into play and serves as validation that our customers are truly feeling it; that it’s not something they can continue to absorb. It’s forcing them to look at different techniques.

Would you say that, while your contractors seem pretty optimistic, they are still behind the eight ball when it comes to certain action items?

If we rewind again to 10 years ago, I don’t think the environment felt so different, but I think that now the industry is in a place where with labor and supply-chain constraints, contractors are needing to make changes. So, I look at that as a glass half full. If over 80% of contractors have an optimistic outlook about AI, but only 40% are implementing it, that 40% is still probably higher than it was 5-10 years ago. That’s a material amount of the market; I’ll take it.

Why is survey and positioning tech some of the most sought after pieces of technology that you found in this survey?

A lot of it comes from what our customers are asking us for, and it’s triangulated based on market research. There’s also an influx of outside investments from the VC and PE community investing in this space which is good for our industry. Every day it’s changing and it’s interesting to see it at the top of the survey list this year.

When it comes to companies either not adopting contech at all, not adopting enough of it, or the right kind, how can the industry as a whole continue to encourage or ramp up the buy-in of this technology?

We need to change behavior, which is hard to do. You still hear, “It’s just the way we’ve operated. This is how we schedule, how the spec is written…” There is a lot that must change. So, we have to encourage people to continue to do more, to commit to the journey.

On the vendor side, to really change behavior, you’ve got to build trust. There’s no doubt that AI can get involved in helping with decision making and automation. But when we do those things with AI, we’ve got to be able to show the vendors how we decided so that they can trust that and see where that recommendation came from.

When it comes to data siloing, one silo of sorts is the 40% of the workforce that’s set to retire. How can the industry ensure that that knowledge isn’t gone when that set of people retire?

If we take a lesson learned in the industry from 15 years ago: They started to build VDC departments, but they kept their normal estimating, scheduling and project management departments, creating an us-versus-them mentality. What we need is the experience from all domains that all these folks leaving have, plus these new folks coming in. The next generation is coming in more accepting of AI, more accepting of 3D and VDC workflows, et cetera. But you’ve got to bring those teams together. If you’re trying to change culture and behavior, you need to merge those folks in. You must use that experience and adopt a new process.

In an earlier conversation, the word ‘democratized’ was used regarding the advancements of scanning and positioning technology. Elaborate on what that means.

The way the industry has historically worked with data is in starts and stops. You design it, you hand it over and then you start to construct it, but often when you hand it over, you lose knowledge. It’s that stair step or see-saw. Every functional area and every stakeholder have their own data and data model. We’ve got to find a way to liberate that data so that it can be used throughout the process. We want the data to be available to everyone across the lifecycle. With new technology, what was once only accessible to bigger, more advanced companies is now also accessible to smaller contractors.

The construction industry’s attitude around AI has already gotten so much better. Would you say the industry is on a cusp when it comes to AI adoption and implementation?

Exactly. That’s why I get so excited when talking about the 40% who are already implementing. That’s very close to 50%. That’s what I need. I don’t need 100% right now. We need 40-50% to make certain moves. And I’ll bet, once the other half sees those moves, they won’t be able to unsee them and they’ll want to make them themselves.

SEE ALSO: THE BENEFITS OF INCORPORATING AI INTO THE CONSTRUCTION LIFECYCLE

The post Trimble Launches New Survey at Annual Dimensions Conference first appeared on Construction Executive.

Construction Technology That Actually Works

Construction technology should target sources of profit loss, such as downtime, rework, budget overruns and safety incidents. Here are proven investments with measurable ROI.

Building Information Modeling

The concept of 3D modeling has been valuable in producing geometric representations of blueprints. Building information modeling takes it a step further by creating and managing extensive project data, including costs, materials and schedules.

Companies can expect better stakeholder collaboration and reduced rework when they connect on these crucial elements and stay aligned. BIM is already expected to increase from $10.27 billion in 2026 to $27.12 billion by 2034 with a CAGR of 12.90%.

Reality Capture and Machine Learning

Reality capture through drones and sensors is versatile, as these tools can be used for site surveys, progress monitoring and safety inspections. Combined with machine learning, progress reports become accurate enough to improve worksite safety for workers.

The collected data can also be used to improve equipment quality and lifespan. Use it as a basis for predictive and preventive maintenance, helping companies experience 52.7% less unplanned downtime than those using reactive maintenance.

Centralized Project Management Software

Centralized project management software can streamline communication, documentation and scheduling all in one platform. A report found that 77% of optimized users saw increased profit margins.

The software also offers productivity gains. By unifying project tasks and enhancing real-time visibility into project progress, construction businesses can reduce their administrative errors and minimize field delays.

Overvalued Tech With Uncertain ROI

As important as technology is, certain buzzwords have innovative potential but are risky or have low ROI. Firms should practice more careful consideration to avoid poor technological investments and implementations.

Metaverse

The metaverse has become more possible through a combination of virtual reality, augmented reality and artificial intelligence. It has the potential to improve virtual visualization and 3D modeling, thereby impacting energy efficiency and reducing construction waste.

However, despite its power, technological limitations and data privacy concerns still hinder its widespread adoption in the construction industry. Investing in it now without proper development might involve little to no return.

Blockchain for Supply-Chain Management

Tracking materials and other resources from a factory to a jobsite can involve numerous documents. Integrating blockchain solutions can boost operational efficiency by 25% while reducing fraud by 50%, which improves transparency between workers and stakeholders.

However, it’s hard to ignore the high implementation costs associated with blockchain. It can also be complex to understand, which isn’t ideal for construction start-ups that may prefer simpler options, such as centralized project management software.

Generative Design

Another application of AI is generative design, which entails creating plans with minimal human input. It’s intended to simplify the planning process, but there are concerns about the unethical use of this technology, given GenAI’s challenges with domain knowledge and model accuracy.

Generative design is prone to hallucination and mistakes. Removing the input of experienced architects and engineers early on in the process can also lead to further delays and expenses in the long run.

How to Choose the Right Technology for the Firm

Differentiating between technological investments that deliver measurable results and those that are simply buzzwords can be challenging. It’s important to take the time to analyze these prospects. Here are tips to help construction industry professionals choose the right ones.

1. Identify Problems Instead of Products

Instead of chasing technological solutions based on what’s popular, focus on what problems the construction business is actually facing. For instance, to improve equipment lifespan, predictive maintenance analytics would be most effective.

Start by defining a problem and then work from there. If there are no clear areas for improvement, take the initiative to identify what would positively impact the company’s profits.

2. Consider the Investment Risks

As high as the ROI may be for certain technologies, it’s still important to understand any risks associated with their implementation. Small- to medium-sized companies, especially, should be vigilant about where they invest their money.

For instance, BIM is ideal for improving planning. However, implementation costs can be relatively high, with some services charging monthly or annual fees, depending on the scale and complexity of the project.

3. Implement a Pilot Project First

Before widespread technology adoption, it’s safe to implement a pilot project first. This will involve a limited number of users to evaluate functionality and gauge the budget and resources required to use the tool effectively. It’s best to have an IT specialist who can help lead its integration.

A pilot project should have a specific timeline and a list of goals that would warrant its implementation. Profitability is a key performance indicator, but it’s also important to assess other elements, such as reduced delays and errors compared to traditional methods.

4. Get Employees Involved Through Training

Incorporating new technologies can become much smoother when employees are involved in the process. Managers should provide adequate training sessions to familiarize construction teams with using these tools, ensuring greater success and better results.

Training can also translate to a more positive evaluation of the pilot project and encourage buy-in from business leaders. Seek their feedback to explore any adjustments in the implementation process when it goes companywide.

Be Intentional With Technology Adoption

Technological adoption should enhance profitability and productivity in the construction industry. Evaluate industry solutions before integrating them into the project process to ensure that upcoming investments have a real impact.

SEE ALSO: EXECUTIVE INSIGHTS 2026: LEADERS IN CONSTRUCTION TECHNOLOGY I

The post Which Construction Technology Investments Actually Move the Needle on Profitability? first appeared on Construction Executive.

But opportunity alone does not guarantee success. As competition intensifies, communication failures and poor information management are emerging as some of the most common (and costly) reasons firms lose margins, miss deadlines or fail to secure repeat work. In data center construction, where schedules are compressed and tolerance for error is minimal, even small breakdowns in communication can have outsized consequences.

Why Data Center Projects Raise the Bar for Communication

Data centers differ fundamentally from traditional commercial construction, particularly when it comes to communication demands. These projects are not simply buildings with specialized tenants. They are mission-critical infrastructure environments where mechanical, electrical and digital systems take precedence, and where mistakes can delay commissioning at enormous cost.

In many data center projects, there is effectively zero tolerance for error. A misrouted duct, an incorrect cable path or an outdated electrical drawing can compromise airflow, redundancy or system performance. Fixing those issues late in the process often requires rework that ripples across multiple trades, extending schedules and increasing risk.

Timelines further heighten the stakes. Data center owners often pursue aggressive schedules to bring capacity online as quickly as possible. Contracts frequently include liquidated damages, meaning every missed day directly erodes profitability. Under these conditions, delays are less likely to stem from physical construction than from slow reviews, unclear approvals or conflicting information.

Confidentiality requirements add another layer of complexity. Data centers are widely considered strategic infrastructure, and owners tightly control access to designs, layouts and system details. Informal communication methods, such as unstructured email chains or unsecured file sharing, can violate contractual obligations and undermine owner confidence.

Stakeholder complexity compounds the challenge. Data center projects typically involve owners, developers, general contractors, specialty subcontractors, equipment vendors, commissioning agents, insurers and authorities having jurisdiction. Each relies on accurate, timely information. When teams lack clarity about which documents are current or which decisions are final, confusion spreads quickly.

Fragmented Communication Creates Real Risk

Despite the high stakes, many construction teams still rely on fragmented communication practices. Drawings live in shared drives, decisions are buried in email threads and approvals are tracked manually. This fragmentation increases the likelihood of errors and makes accountability difficult to establish.

Version control is a frequent failure point. When different team members reference different iterations of drawings or models, coordination errors multiply. In a data center environment, those errors can halt progress entirely.

Documentation practices also reveal a firm’s maturity. Data center commissioning requires complete, accurate records, including as-built drawings, testing results, warranties and operations manuals. Teams that delay documentation until the end of the project often scramble to assemble information, delaying handover and straining relationships with owners.

Just as importantly, communication practices directly affect reputation. Owners in the data center market tend to favor partners with proven reliability. A clear, defensible record of decisions, changes and approvals builds trust and reduces disputes. Conversely, missed deadlines, unresolved RFIs or incomplete documentation quietly damage credibility and can result in firms being excluded from future bid opportunities.

Workforce Constraints Make Communication Even More Critical

Communication challenges are intensifying as labor shortages strain the construction industry. Data center projects require specialized skills, including commissioning engineers and power systems experts. These roles are difficult to fill, yet demand continues to rise.

With limited talent available, firms cannot scale simply by adding people. Instead, they must improve how work is managed. Clear workflows, centralized information and disciplined communication allow smaller teams to handle more complex projects without sacrificing quality.

Strong information management also reduces dependency on institutional knowledge held by a few individuals. When project history is captured systematically, teams remain resilient even as personnel change.

Practical Steps to Avoid Costly Communication Failures

Firms looking to compete effectively in the data center market must treat communication as a core operational function. Several practices consistently distinguish high-performing teams:

• Centralize information. Establish a single source of truth for drawings, correspondence, RFIs and submittals. Centralization reduces confusion and minimizes version conflicts, ensuring all stakeholders are working from approved information.
• Standardize workflows. Defined processes for reviews, approvals and changes prevent bottlenecks and clarify responsibility. Automated routing and status tracking can help teams identify issues before they impact schedules.
• Build security into collaboration. Role-based access controls and secure sharing protocols are essential for protecting sensitive information and meeting confidentiality expectations.
• Document progressively. Collect and organize documentation throughout the project rather than at the end. Progressive documentation supports smoother commissioning and faster, cleaner handovers.
• Integrate systems where possible. Disconnected tools increase the risk of misalignment. A full integration improves consistency and reduces duplicate data entry.

Some organizations use dedicated platforms, like Newforma, to support these practices, but the underlying principle applies regardless of technology. Discipline, transparency and accountability matter more than any individual tool.

Communication as a Competitive Advantage

The data center boom shows no signs of slowing. Energy demand is rising, digital infrastructure investment is accelerating and owners are becoming more selective about who they trust to deliver. In this environment, communication failures are not minor inconveniences, but strategic liabilities.

Construction firms that invest in clear communication, secure collaboration and disciplined information management position themselves to win repeat work and protect margins. Those that do not risk being left behind, not because demand disappeared, but because confidence did.

In data center construction, execution defines success. That kind of success requires communication that is simple, secure and reliable from start to finish.

SEE ALSO: DATA CENTER SURGE: PRE-DEVELOPED SPACE ALREADY 90% LEASED

The post Communication Gaps Can Cost Construction Firms in the Data Center Boom first appeared on Construction Executive.

One common thread links both problems: Documentation gaps turn minor issues into major disputes.

When issues pull teams away from higher-value work, visual site documentation, especially 360° imagery, is shifting from a nice-to-have to a strategic safeguard. Captured consistently and linked to location and time, 360° documentation strengthens risk mitigation, supports compliance, speeds dispute resolution and helps teams deliver higher-quality outcomes across the full building lifecycle.

The Documentation Gap: Why Traditional Methods Fail

Most site teams already take photos. The problem instead is that conventional documentation often fails under pressure because it is hard to retrieve when needed most.

The pattern repeats across projects:

• Fragmented storage across photos, emails, paper logs and shared drives
• Limited context in standard photos that show detail(s) but not the surrounding conditions
• Inconsistent formats across stakeholders, including subcontractors and third parties
• Slow retrieval during inspections and audits
• Weak defensibility when key phases were not documented clearly

Records can exist and still be unusable. When an owner or insurer asks for proof of an inspection step, or when subcontractor disputes come down to “Who did what when?” teams can lose days searching for information or relying on memory and partial notes. When documentation processes add a layer of risk, it is the way visual information is captured that needs to be reworked.

What 360° Visual Documentation Changes

A 360° capture builds a continuous record of the site. Instead of a single photo that shows details in isolation, 360° imagery creates a time-stamped record of what was built, where it was built and what else was happening at that point.  Beyond capturing the site, documentation must be standardized across teams ensuring formats stay consistent and site data is stored in one place. With full context and a defined structure, teams can build compliance reports quickly and retrieve supporting evidence without a time-consuming search.

Stronger Risk Mitigation and Fewer Disputes

Claims often hinge on proof, sequencing or installation quality. Gaps in proof create ambiguity, which leads to disputes in predictable scenarios:

• Subcontractor responsibility disputes (what was complete when the next trade started)
• Delay claims tied to access constraints or work-area readiness
• Defect allegations where workmanship is questioned after walls close
• Warranty discussions that depend on installation conditions at handover

Consistent 360° visual documentation reduces ambiguity by showing site conditions and progress status in a single view. The discipline matters as much as the technology. When contractors capture sites consistently, disputes shift from memory-based arguments to fact-based conversations about documented conditions.

Better Compliance and Inspection Readiness

Regulators want visual proof that safety steps were completed. Insurers want transparent records to evaluate risk management and, in some cases, to shape coverage terms. Paper-based logs and disconnected systems slow teams down during audits. Digital documentation helps by centralizing workflows, which reduces errors and ensures documentation is continuous. A structured digital record can be pulled into a report in seconds. 360° capture strengthens compliance records by showing full context: not just what was installed, but what surrounded it and what stage the work was in.

Higher Quality and Less Rework

Rework is expensive because it pulls labor off planned work and creates downstream schedule impacts. A consistent 360° record helps teams track progress at each stage and compare conditions over time before they are concealed behind walls or ceilings. Later, during troubleshooting, teams can review what was installed at a specific phase without opening walls. Side-by-side comparisons between two dates show exactly when something changed, which speeds issue resolution.

How 360° Capture Fits Into Standard Workflows

To protect margins and reduce exposure, successful teams treat 360° capture as part of routine site workflows, not a separate task. Field teams walk a floor or zone with a helmet-mounted camera on a predictable schedule, then upload the imagery to a central project record where it is pinned to plans and timestamped.

When capture is consistent, it becomes useful across quality assurance, safety, progress tracking, owner reporting and closeout. Features like PlanRadar’s SiteView, for example, pair 360° walks with AI algorithms to automatically map imagery to 2D floor plans, so teams can access site areas by location rather than scrolling through folders.

Structured Data: The Foundation for AI-Assisted Workflows

As teams capture more site data, structure becomes critical. When documentation is stored consistently, tagged the same way, pinned to plans, centralized in one system, AI can retrieve information in seconds instead of hours.

This enables AI-supported capabilities like:

• Search across captured project data to find relevant records faster
• Automated project overviews generated from current field documentation
• Faster retrieval of critical information during audits, inspections or claims
• Earlier visibility into risks and patterns, such as repeat issues by location or trade

The payoff depends on fundamentals. Structured documentation today creates the foundation for AI-assisted insights tomorrow.

Documentation as a Competitive Advantage

In short, 360° documentation is risk management. It helps contractors prove what happened on a project, which supports compliance, strengthens quality control and reduces uncertainty when stakeholders disagree. When project data is structured, centralized and time-stamped, AI can surface insights in seconds, turning documentation into actionable clarity.

As projects grow more complex and regulatory expectations rise, the contractors who thrive will not be the ones with the most photos. They will be the ones who can prove what happened, when it happened and what else was happening at the same time, in seconds, not days. That’s documentation as a competitive advantage. 

SEE ALSO: THE REALITY OF IMPLEMENTING VR/AR ON THE JOBSITE

The post Full Project Transparency: Why 360° Documentation Is Becoming Essential on Modern Construction Sites first appeared on Construction Executive.

“The research indicates the construction industry is nearing a tipping point for AI adoption,” says Steve Jones, senior director of industry insights at Dodge Construction Network, who sat down with Construction Executive to delve further into the survey questions and answers and what the industry’s current position on them means for AI’s future role in construction.

Other results worth noting include:

• 85% of contractors expect they will spend less time on repetitive, mundane tasks
• Over 70% believe they can make better decisions because AI offers insights they might not arrive at on their own
• 75% look ahead to AI helping them learn from past projects by mining historical data
• 40% are currently allocating a dedicated budget to AI
• 38% are creating implementation teams
• 19% report adapting legacy workflows for an AI environment
• 51% are actively evaluating several potential AI-related changes across their teams
• 81% recognize the benefit of automated constructability analysis to identify potential field issues during design
• 80% express interest in intelligent permit submission with automatic compliance checking
• 79% note strong potential for autonomous project optimization that adjusts schedules and resources in real time
• 76% identify opportunities in dynamic pricing optimization based on market conditions and risk factors
• 92% acknowledge the value of automated contract creation and management
• 79% value intelligent bid-no-bid decision support

The overall findings seem overwhelmingly optimistic. Was that surprising?

No, because there’s already so much in the general consumer environment about AI. It’s very different than when BIM came out—because that wasn’t widely talked about; you had to be in the industry to even have heard of it and it was easily dismissed as just another form of 3D. But now AI is so wide and there probably isn’t anybody who answered our survey who isn’t already also using ChatGPT or Claude or one of these LLMs. They know how it functions, what it does, and they’ve heard so much about it.

I expected the job loss question to score pretty highly in terms of concern—I was pleased to see that that was pretty low, around 20%. I think we may have gotten over that concern.

For the last two years I’ve been pushing to call it augmented intelligence instead of artificial intelligence. AI is here to help us all be better and faster. It isn’t here to replace anybody.

The survey shows 85% of contractors expect they will spend less time on repetitive, mundane tasks. It’s surprising that that’s not 100%. It that because contractors don’t expect AI to be able to automate everything?

There are certain repetitive tasks that don’t lend themselves to AI. It will be interesting to come back to a study like this two or three years from now asking similar questions and compare answers. The answer may be 99% at that point, but at the end of the day, AI’s not going to dig a ditch for you. But there is a robot that’s going to dig that ditch. And the robot will be powered by AI.

Would you say AI is creating opportunities for more jobs rather than replacing workers?

I don’t know that it’s creating the opportunity for more jobs, but what it’s going to be able to allow people to do is contend with the resource strain and drain from the workforce shortage that isn’t going away. The combination of AI automating mundane tasks and robotics being able to actually do labor will help people become much better decision makers.

Only 40% of those surveyed are allocating a budget for AI. Is it that people can’t yet afford these full tech stacks? Or is there just not enough buy-in to AI in general?

There still seems to be a general wait-and-see attitude. People like to know they’re not alone in whatever it is they’re doing. We can say, ‘Here is what a hundred other folks who look a lot like you are doing with this and what’s working and what isn’t working.’ So, they can have the confidence to move forward.

With AI, once people are in the game, they like to play the game and they don’t know why they didn’t start playing earlier. So, how fast do you see the number of players increasing by the end of the decade?

I think it’s longer than that. Because even as big as AI already is, construction is a people business at the end of the day. Human beings have to make the decision to get in the pool and how far down towards the deep end to swim. It’s such a fragmented and growing business right now, nobody has very much time to put energy into something that would seem extracurricular.

If you look at this industry 15 years from now, it will look dramatically different than it does today. But I don’t think the next four or five years are going to show that much. We will begin to see greater preparation, much more engagement and awareness. And I think we’ll see a similar pattern of those who have gotten into the game and are using AI saying that it’s great. The vendors need the feedback coming from the users. The more people who’re using AI, the more feedback they can give and then the better the vendors can make those tools function. The function of AI already far outpaces what construction’s ready for now.

SEE ALSO: MORE CONSTRUCTION COMPANIES ARE BUILDING A TECHNOLOGY-FOCUSED C-SUITE

The post New Survey Reveals Overwhelmingly Optimistic Results on the Use of AI in Construction first appeared on Construction Executive.

Construction as a Technology Leader

One of the defining moments of CES 2026 came during Caterpillar’s keynote address. CEO Joe Creed addressed a packed room with a question many may have been thinking: “Why is a construction equipment company delivering a keynote at CES?”

The answer became evident quickly. Modern construction equipment is no longer just mechanical—it is digital, autonomous, connected and powered by sophisticated technology stacks. Caterpillar announced five autonomous construction vehicles and demonstrated Level 4 autonomy capabilities. The shift underway is significant: Operators are transitioning from inside the cab to remote environments where fleets can be managed simultaneously. Perhaps the most notable unveiling was the CAT AI Assistant, scheduled to go live in Q1 2026. During a live demonstration, a simple voice command adjusted an electrical line warning height to 13 feet. The assistant integrates speech, text and image recognition—representing a move toward multimodal AI systems that assist real-time field operations. Construction is no longer simply adopting technology—it is helping define how technology is applied in the physical world.

A Connected Equipment Ecosystem

Across the LVCC West Hall, the evolution of heavy equipment was unmistakable.

Oshkosh and JLG showcased paired scissor lifts engineered specifically for lifting structural steel—an example of equipment designed around task optimization rather than generalized capability. John Deere continued expanding its autonomous ecosystem, reinforcing the trend toward intelligent fleet coordination.

Battery innovation companies, including Lyten, demonstrated advances in energy density and battery chemistry, highlighting that electrification is moving beyond experimentation and toward jobsitewide energy strategies.

Electrification discussions at CES 2026 extended beyond machines themselves. Charging infrastructure, energy management systems and power optimization software were part of the broader narrative. As cities push for lower emissions and reduced noise pollution, electric equipment is becoming a practical solution for urban and indoor projects.

It is no longer just about whether electric machines can perform—it is about how entire jobsites can be powered efficiently and sustainably.

Innovation from Startups: Solving Field-Level Problems

The Venetian’s Eureka Park, home to emerging startups, provided a view into construction’s next wave of innovation.

Autodesk demonstrated advancements in component modeling, reinforcing the growing integration between design intelligence and field execution. As digital models become more detailed and connected to real-world data, the gap between virtual planning and physical construction continues to shrink.

Cosito introduced AI-powered voice and sensor technology capable of automatically generating daily reports and field documentation. For an industry burdened by administrative paperwork, automation in this space could unlock significant productivity gains.

MIMO Detect presented underground pipe detection technology using ground-penetrating radar. While still in prototype phase and currently stronger in horizontal positioning than depth accuracy, the technology reflects ongoing efforts to reduce subsurface risk and prevent costly utility strikes. 

What stood out across the startup ecosystem was focus. Solutions were not speculative—they were targeted at real-world construction challenges: documentation, detection, visualization and efficiency.

Robotics and Spatial Computing

Robotics once again drew attention throughout the North Hall, with humanoid platforms, quadrupeds and service robots on display. However, the emphasis has shifted from novelty to application.

Exoskeleton technologies continue improving in wearability and ergonomic support, aiming to reduce strain injuries and extend workforce longevity. AI hardware companies such as DeepX demonstrated embedded processing systems powering autonomous vision and robotics applications. One particularly compelling development was spatial computing integrated through hard hat-mounted camera systems. By capturing and processing real-time visual data from a worker’s perspective, these systems aim to enhance hazard detection, progress tracking, and documentation. Robotics at CES 2026 felt less like spectacle and more like support—tools designed to augment skilled workers rather than replace them.

Workforce and AI Literacy

Technology alone does not build infrastructure—people do. Several CES sessions focused on preparing the workforce for rapidly evolving tools.

In the session “Next Gen Skills: Preparing Students for Tomorrow’s Tech,” leaders from Amazon, Oshkosh, CTA, and Tech Access emphasized AI literacy as a foundational skill. Amazon has committed $2.5 million to certify students in AI education and pledged to prepare four million students to use AI by 2028. Apprenticeship models are expanding to support data center construction and advanced infrastructure projects.

Key themes included:

• Prompt engineering as an emerging skill
• Understanding how to work alongside AI agents
• Collaboration between industry and education
• Ensuring technology remains accessible

Construction faces ongoing labor shortages and safety challenges. With less than 5% of the workforce employed in construction but accounting for nearly 20% of safety incidents, AI-powered safety systems and automation could play a transformative role.

New roles are already emerging: fleet autonomy managers, digital twin specialists, AI operations coordinators and construction data analysts. Preparing for jobs that do not yet fully exist is becoming part of the industry’s responsibility.

Connectivity: The Infrastructure Behind Innovation

Discussions involving FCC and NTIA leadership highlighted another critical factor: connectivity. Universal broadband access, spectrum policy, 6G development and WiFi 7 readiness are not abstract regulatory topics — they are foundational to connected construction ecosystems. Autonomous fleets, remote equipment management, real-time drone processing and AI-driven safety systems all depend on reliable, high-speed networks. As infrastructure becomes smarter, connectivity becomes as important as concrete and steel.

Lingering Thoughts Towards a Shift in Equipment Design

In conversations with industry leaders, an intriguing idea surfaced: As autonomy advances, equipment design itself may fundamentally change. If machines no longer require operators in cabs, what happens to traditional controls? Do we eliminate joysticks, operator compartments, and certain mechanical components altogether?

Autonomy does not just change how machines operate—it may redefine how they are built.

Looking Ahead

CES 2026 demonstrated that construction technology is no longer niche. It is integrated across AI, robotics, electrification, manufacturing and policy.

The industry is entering a phase where digital intelligence and physical infrastructure are inseparable. One key takeaway resonated: Technology should be deployed to solve problems, not simply to showcase innovation. That principle applies directly to construction. Adoption must be strategic, measurable and outcome-driven.

Autonomous fleets, AI assistants, spatial computing, electrified equipment and workforce AI literacy initiatives are not distant visions—they are active deployments.

Construction is not standing on the sidelines of innovation. It is helping build it.

SEE ALSO: HOW MOBILE TOOLS ARE CAPTURING SAFETY DATA ON JOBSITES

The post Building the Future: Construction at the Center of Technological Innovation at CES 2026 first appeared on Construction Executive.

1. GOVERANCE AS A GUARDRAIL

Most firms are already piloting AI tools to update schedules, manage supply chains and monitor jobsite safety in real time. But these systems are only as reliable as the data they access.

Shifting from manual cleanup to AI-powered data governance is essential. Environments filled with redundant, outdated or trivial data increase the risk of AI “hallucinations” or accidental exposure of sensitive project, contract or employee information. Industry reports show that up to 55% of stored data falls into this category. Automating data inventory, archiving and deletion helps ensure AI tools operate on clean, secure datasets.

2. PROJECT-BASED USER ACCESS

Today’s biggest cyber threat is often not a hacker, but a dormant account. Workforce turnover, subcontractor access and shifting project teams create risk when permissions linger. Former employees and contractors remain common entry points for ransomware.

Digital access should mirror physical jobsite access: time-limited, role-specific and automatically revoked when a project ends. Pairing a least-privilege model with mandatory multi-factor authentication—which can block nearly all automated attacks—significantly reduces exposure.

3. AUDITING THE INVISIBLE THREAT

Strong cyber hygiene is now a competitive advantage, especially on projects involving sensitive data. Treat digital risk like a jobsite hazard, with regular audits to surface issues early.

Ransomware resilience does not require sweeping system overhauls. It requires discipline, clear policies and consistent review. Data risk is project risk, and managing it with the same rigor ensures firms stay resilient and ready to build.

SEE ALSO: CYBERSECURITY FOR CONTRACTORS—INCLUDING HOW TO MITIGATE CYBER ATTACKS

The post Cyber, Secured: Cybersecurity Beyond the IT Team first appeared on Construction Executive.